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研究生:李易學
研究生(外文):Yi-Hsueh Lee
論文名稱:無線射頻與視覺定位演算法之實現
論文名稱(外文):Development of an RF-Vision Positioning Algorithm
指導教授:莊智清莊智清引用關係
指導教授(外文):Jyh-Ching Juang
學位類別:碩士
校院名稱:國立成功大學
系所名稱:電機工程學系專班
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2009
畢業學年度:97
語文別:中文
論文頁數:68
中文關鍵詞:視覺定位射頻定位
外文關鍵詞:Vision-localizationRF-localization
相關次數:
  • 被引用被引用:1
  • 點閱點閱:150
  • 評分評分:
  • 下載下載:13
  • 收藏至我的研究室書目清單書目收藏:2
定位是無線感測網絡的一個重要主題,能行使位置服務等運用。在室內環境中依靠射频量測,並依據訊號强度、到達時間(TOA)或到達角度(AOA)任一種方式定位,是眾所皆知的方法之一。特别的是基於射頻訊號强度(RSS)的方法有著隨手可得的量測資訊與廉價實現的優點而引人注目。但基於RSS定位的方法容易受到多路徑效應、訊號衰退、干擾…等環境因素所影響。本論文中,提出了融入於射頻系統的視覺系統,建立了強健性的定位功能。 在這結合射頻與視覺的架構下, 射頻系統提供資料傳輸,來源辨別,且粗糙式的量測方式,而視覺系統讓追蹤來源的功能更加完美。同時,可以簡化視覺資訊的計算處理,並且定位將更加的準確。 本論文所提出的研究方法經由移動機器人在室內環境的節點定位實驗所驗證。
Localization is an important topic in wireless sensor networks and location-based services. A well-known method for localization in indoor environment is to rely on radio frequency measurements in terms of signal strength, time-of-arrival, and/or angle-of-arrival. In particular, the received signal strength (RSS) based method is attractive due to its readily-available measurements and low-cost implementation. However, the RSS based method is subject to environmental effects such as multipath, fading, and interference. In the thesis, a vision system is fused with the RF system is establish a robust localization capability. Under this RF-vision framework, the RF system provides data communication, source identification, and coarse-range measurement and the vision system facilitate fine source tracking capability. Together, the visual signal processing tasks can be simplified and the location can be determined more accurate. The proposed approach is verified through a mobile robot tracking experiment in an indoor environment.
摘 要 I
Abstract II
目錄 III
圖目錄 VI
表目錄 VIII
第一章 緒論 1
1.1 前言 1
1.2 研究動機與方法 1
1.3 文獻回顧 2
1.4 主要貢獻 3
1.5 論文架構 3
第二章 無線射頻定位演算法 4
2.1 ZigBee 無線通訊技術 4
2.2 訊號品質之特性分析 6
2.2.1 訊號品質變動的因子 6
2.2.2 能量與路徑衰減模型 7
2.3 基於射頻之定位演算法 8
2.3.1 無線訊號三邊定位 8
2.3.2 無線訊號特徵比對定位 10
2.4 權重質心定位(Weighted Centroid Localization) 12
2.4.1 質心定位 12
2.4.2 權重質心定位 13
2.5 定位模擬結果分析 14
2.5.1 模擬設定 15
2.5.2 結果與分析 17
第三章 影像處理與定位 22
3.1 前言 22
3.2 彩色影像辨識系統 23
3.2.1 色彩空間 23
3.2.2 區塊掃描之雜訊濾除 26
3.2.3 聚類成長演算法 26
3.3 相機幾何與電腦視覺基礎理論 29
3.3.1 攝影機模型 30
3.3.2 重建世界座標的位置 35
3.4 結合無線射頻與視覺定位系統 37
第四章 模糊控制器之運動控制 42
4.1 簡介 42
4.2 輪型機器人之動態系統描述 43
4.3 如何設計運動控制器 44
4.4 模糊滑動模態控制器 45
4.4.1 模糊滑動模態控制器之設計 45
4.4.2 模糊滑動模態控制器之影響因子 47
4.4.3 分析結果 49
第五章 系統實現與實驗結果分析 51
5.1 無線感測模組 51
5.2 輪型機器人 53
5.3 系統架構 54
5.4 伺服端程式 56
5.5 定位實驗建構 57
5.5.1 定位實驗 57
5.5.2 實驗結果分析 58
第六章 結論與未來工作 63
6.1 結論 63
6.2 未來工作 64
參考文獻 65
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